Kidnapped laser-scanner for evaluation of RFEC tool

Falque, R; Vidal-Calleja, T; Miro, JV

Kidnapped laser-scanner for evaluation of RFEC tool

Falque, R Vidal-Calleja, T

Miro, JV

Permalink

Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2015, 2015-December pp. 313 - 318
Issue Date:: 2015-12-11

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (1.53 MB)

Adobe PDF

Download Accepted Manuscript versionAdobe PDF (1.45 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Falque, R	en_US
dc.contributor.author	Vidal-Calleja, T https://orcid.org/0000-0002-5763-9644	en_US
dc.contributor.author	Miro, JV https://orcid.org/0000-0002-0083-7797	en_US
dc.date.issued	2015-12-11	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2015, 2015-December pp. 313 - 318	en_US
dc.identifier.isbn	9781479999941	en_US
dc.identifier.issn	2153-0858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/37785
dc.identifier.uri	http://hdl.handle.net/10453/37467
dc.description.abstract	© 2015 IEEE. An algorithm is proposed for matching data from different sensing modalities. The problem is formalised as a kidnapped robot problem, where Bayesian fusion is used to find the most likely location where both modalities agree. The key idea of our algorithm is to model the correlation between the two modalities as a likelihood used to update a location prior. Data, in this case, is represented as 2.5D thickness maps from a laser scanner and a Remote Field Eddy Current (RFEC) tool, used in non-destructive testing to assess the condition of infrastructures. The laser data is limited, while RFEC data is continuous. Given some prior in location, the aim is to find the 2.5D thickness map from the laser that corresponds to the RFEC data, which should be noted is highly noisy. Real data from CCTV inspections of water pipes are used to validate the proposed approach.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2015.7353391	en_US
dc.title	Kidnapped laser-scanner for evaluation of RFEC tool	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2015-December	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	Hamburg, Germany
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2015-December	en_US

Abstract:

© 2015 IEEE. An algorithm is proposed for matching data from different sensing modalities. The problem is formalised as a kidnapped robot problem, where Bayesian fusion is used to find the most likely location where both modalities agree. The key idea of our algorithm is to model the correlation between the two modalities as a likelihood used to update a location prior. Data, in this case, is represented as 2.5D thickness maps from a laser scanner and a Remote Field Eddy Current (RFEC) tool, used in non-destructive testing to assess the condition of infrastructures. The laser data is limited, while RFEC data is continuous. Given some prior in location, the aim is to find the 2.5D thickness map from the laser that corresponds to the RFEC data, which should be noted is highly noisy. Real data from CCTV inspections of water pipes are used to validate the proposed approach.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/37467